Bynd 2.3

Bynd is a way of introducing static typing to Python.

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A module which allows binding data to a single type.

Bynd's intended use, is to be assigned to a variable.

Which, in this case, the variable can still be used

exactly the same by creating a Bynd reference object

and invoking the 'byndref' method, then invoking the

'data' method. Since data is bound to a single type

the data cannot be modified causing it to become constant

and forces the programmer to create Bynd object instance

references that can be modified. Inner collection types

can be specified using the 'inner' keyword argument and

passing it a 'set' of types, to which the collection

elements will be bound.

The benefits of using Bynd are:

1. Runtime type checking

2. Constant Bynd object instance data

3. Bynd object instance references

4. Ability to access all data associated with a Bynd instance through a 'ByndRef' by invoking any of the reference methods such as: 'data', 'kind', 'inner', and 'info' after a Bynd reference is created

5. Ability to modify reference data according to the previously specified types. This means that any new data must be inline with the types specified in the original Bynd object instance.

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Bynd: Basic Usage

# filename: Bynd_test.py
from Bynd.bynd import Bynd

# Instantiates a Bynd object and binds the data [1,2,[3,4,5]] to the type 'list'
# and it also binds the inner elements to the type 'list' and 'int' for both lists
my_variable = Bynd([1, 2, [3, 4, 5]], list, inner={list, int})  # the data can't be changed

# The above code will raise a 'ByndError' if the data is not of type 'list'
# and if the inner elements are not of type 'list' or 'int'

# To access the data, we need to create a 'ByndRef' (a reference to a Bynd object instance).
my_varaible_ref = my_varaible.byndref()

# We can now access and print the data.
print("my_variable_ref.data: ", my_variable_ref.data())

# The 'data' and 'types' can be accessed using the 'info' method.
print("my_variable_ref.info: ", my_variable_ref.info())

# Output:
#    my_variable.data: "[1, 2, [3, 4, 5]]"
#    my_varaible.info: [([1, 2, [3, 4, 5]], <class 'list'>, {<class 'list'>, <class 'int'>})]

# Bynd reference data can also be modified as long as the data is inline with the types
# specified in the original Bynd instance (my_variable). To do so, we need to invoke the
# 'modify' method on the reference. Remember that the data is bound to the 'list' type and
# 'inner' contains the 'list' and 'int' types which means our new data needs to have at least
# one integer and/or list.
my_variable_ref.modify([300, 400, [10, 20, 30]])

# Now, lets print the new data.
print("my_variable_ref.data: ", my_variable_ref.data())
print("my_variable_ref.info: ", my_variable_ref.info())

# output:
#   my_variable_ref.data: [300, 400, [10, 20, 30]]
#   my_variable_ref.info: ([300, 400, [10, 20, 30]], list, {<class 'list'>, <class 'int'>})

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NOTE:

Bynd, automatically performs recursive type checking. What that means is, for any

collection type (list, tuple, set, etc.) it encounters, collection element types

are checked against the type set passed to inner. All types need to be known or assumed

when using 'Bynd'. It also does not make use of type hints in any way and it introduces

strict yping to Python by striping some of its flexibility. Bynd, can be used along side

type hints and can be used as a way to enforce them.

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